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Energy Consumption Forecasting for Smart Meters Using Extreme Learning Machine Ensemble.

Sensors (Basel, Switzerland)
The employment of smart meters for energy consumption monitoring is essential for planning and management of power generation systems. In this context, forecasting energy consumption is a valuable asset for decision making, since it can improve the p...

Keratoconus Severity Classification Using Features Selection and Machine Learning Algorithms.

Computational and mathematical methods in medicine
Keratoconus is a noninflammatory disease characterized by thinning and bulging of the cornea, generally appearing during adolescence and slowly progressing, causing vision impairment. However, the detection of keratoconus remains difficult in the ear...

Comparing linear and non-linear data-driven approaches in monthly river flow prediction, based on the models SARIMA, LSSVM, ANFIS, and GMDH.

Environmental science and pollution research international
River flow variations directly affect the hydro-climatological, environmental, and ecological characteristics of a region. Therefore, an accurate prediction of river flow can critically be important for water managers and planners. The present study ...

Prediction of irrigation groundwater quality parameters using ANN, LSTM, and MLR models.

Environmental science and pollution research international
Forecasting the irrigation groundwater parameters helps plan irrigation water and crop, and it is commonly expensive because it needs various parameters, mainly in developing nations. Therefore, the present research's core objective is to create accu...

Sensing small interaction forces through proprioception.

Scientific reports
Understanding the human motor control strategy during physical interaction tasks is crucial for developing future robots for physical human-robot interaction (pHRI). In physical human-human interaction (pHHI), small interaction forces are known to co...

Prediction of the chromatographic hydrophobicity index with immobilized artificial membrane chromatography using simple molecular descriptors and artificial neural networks.

Journal of chromatography. A
Screening of physicochemical properties should be considered one of the essential steps in the drug discovery pipeline. Among the available methods, biomimetic chromatography with an immobilized artificial membrane is a powerful tool for simulating i...

Sensorless Estimation Based on Neural Networks Trained with the Dynamic Response Points.

Sensors (Basel, Switzerland)
In the present work, a neuronal dynamic response prediction system is shown to estimate the response of multiple systems remotely without sensors. For this, a set of Neural Networks and the response to the step of a stable system is used. Six basic c...

Simulation and Prediction of Fungal Community Evolution Based on RBF Neural Network.

Computational and mathematical methods in medicine
Simulation and prediction of the scale change of fungal community. First, using the experimental data of a variety of fungal decomposition activities, a mathematical model of the decomposition rate and the relationship between the bacterial species w...

Predicting crop root concentration factors of organic contaminants with machine learning models.

Journal of hazardous materials
Accurate prediction of uptake and accumulation of organic contaminants by crops from soils is essential to assessing human exposure via the food chain. However, traditional empirical or mechanistic models frequently show variable performance due to c...